Initial condition of costate in linear optimal control using convex analysis

Automatica ◽  
2011 ◽  
Vol 47 (4) ◽  
pp. 748-753 ◽  
Author(s):  
Bin Liu
Keyword(s):  
Optimal Control ◽  
Convex Analysis ◽  
Initial Condition ◽  
Linear Optimal Control

Optimal control of a hyperbolic system that describes Slutsky demand

2021 ◽  
pp. 58-59
Author(s):  
Olha Milchenko
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Hyperbolic System ◽  
Method Of Characteristics ◽  
Social Processes ◽  
Computational Algorithms ◽  
Initial Condition ◽  
Linear Optimal Control ◽  
First Order

A non-linear optimal control problem for a hyperbolic system of first order equations on a line in the case of degeneracy of the initial condition line is considered. This problem describes many natural, economic and social processes, in particular, the optimality of the Slutsky demand, the theory of bio-population, etc. The research is based on the method of characteristics and the use of nonstandard variations of the increment of target functional, which leads to the construction of efficient computational algorithms.

Frequency Shaped Linear Optimal Control with Transfer Function Riccati Equations

1984 ◽  
Vol 17 (2) ◽  
pp. 287-292
Author(s):  
J.B. Moore ◽  
B.D.O. Anderson ◽  
D.L. Mingori
Keyword(s):  
Optimal Control ◽  
Transfer Function ◽  
Riccati Equations ◽  
Linear Optimal Control

scholarly journals THE THEORY AND APPLICATION OF LINEAR OPTIMAL CONTROL

1966 ◽  
Author(s):  
Edmund G. Rynaski ◽  
Richard F. Whitbeck
Keyword(s):  
Optimal Control ◽  
Linear Optimal Control

Sequential Monte Carlo methods for diffusion processes

2009 ◽  
Vol 465 (2112) ◽  
pp. 3709-3727 ◽  
Author(s):  
Ajay Jasra ◽  
Arnaud Doucet
Keyword(s):  
Optimal Control ◽  
Monte Carlo ◽  
Option Pricing ◽  
Monte Carlo Methods ◽  
Sequential Monte Carlo ◽  
Diffusion Processes ◽  
Time Discretization ◽  
Initial Condition ◽  
Sequential Monte Carlo Methods ◽  
Low Dimensional

In this paper, we show how to use sequential Monte Carlo methods to compute expectations of functionals of diffusions at a given time and the gradients of these quantities w.r.t. the initial condition of the process. In some cases, via the exact simulation of the diffusion, there is no time discretization error, otherwise the methods use Euler discretization. We illustrate our approach on both high- and low-dimensional problems from optimal control and establish that our approach substantially outperforms standard Monte Carlo methods typically adopted in the literature. The methods developed here are appropriate for solving a certain class of partial differential equations as well as for option pricing and hedging.

Linear Optimal Control for Reentry Flight

1994 ◽  
pp. 339-348 ◽  
Author(s):  
Axel J. Roenneke ◽  
Klaus H. Well
Keyword(s):  
Optimal Control ◽  
Linear Optimal Control
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